Generating Symbolic Business Processes in Support of Evaluating Process Optimization

Research in business process optimization is valuable in improving business process models. However, it is difficult to find real datasets of business processes to evaluate process improvement techniques and tools. In this paper, a symbolic process generator, namely G-DCBP, is introduced to stochastically generate symbolic data-centric business processes that can be used to analyze their properties and evaluate optimization approaches according to end-users' specification.